import pandas as pd




def clean_df(df, training=True):
    df = df.drop(['site_id', 'app_id', 'device_id', 'device_ip', 'site_domain',
                  'site_category', 'app_domain', 'app_category', 'device_model'], axis=1)
    if training:
        # id column is not required for training purposes
        df = df.drop(['id'], axis=1)

    return df

def load_df(filename, training=True, **csv_options):
    # df = pd.read_csv(filename, header=0, nrows=100000, **csv_options)
    # df = pd.read_csv(filename,  nrows=100000, **csv_options)
    df = pd.read_csv(filename, header=0, **csv_options)

    # df.head()
    # print(df.head())
    # print("**********************************************************************")

    #df.describe()
    # print(df.describe())
    # print("**********************************************************************")
    #
    # df.info()
    # print("**********************************************************************")

    df = clean_df(df, training=training)
    return df
